Artificial Intelligence Based Speed Control of SRM for Hybrid Electric Vehicles

A Switched Reluctance Motor (SRM) is a robust electrical motor which have features that qualifies to be used in electric vehicle and aerospace application due to its simple construction. SRM drive has acquired an expanding enthusiasm in hybrid electric vehicle applications because of its high efficiency, reliability, robust structure and reduced rotor losses. However, current and torque ripples are major drawbacks in this type of motor for electric car application. In order to reduce the ripple contents for controlling the speed of the SRM drive, various control techniques are designed using simulation software. The target of this work is to look at the operation of Fuzzy logic, Adaptive-Neuro Fuzzy Inference Strategy (ANFIS) and Direct Torque Controller (DTC) to highlight performance of effective controller. The result of applying DTC technique to a SRM drive gives the high robustness and better performance than a conventional fuzzy logic and ANFIS design technique. Simulation work is carried out using Simulink environment.